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Sex Differences in Gut Microbiome Dysbiosis between Individuals with or without Cardiovascular Disease
Author(s) -
Aryal Sachin,
Manandhar Ishan,
Joe Bina,
Cheng Xi
Publication year - 2021
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.2021.35.s1.02444
Subject(s) - dysbiosis , microbiome , disease , gut flora , biology , akkermansia , bacteroides , medicine , immunology , bioinformatics , genetics , bacteria
Cardiovascular disease (CVD), as one of the leading causes of death worldwide, represents various morbid conditions such as hypertension and atherosclerosis. As gut microbial dysbiosis has been reported in patients with different types of CVD, we previously analyzed large‐scale gut microbiome data of CVD and non‐CVD human subjects and reported a gut microbiome‐based machine learning strategy for discriminating the CVD and non‐CVD subjects. In this study, we further hypothesized that sex is a discriminative factor in gut microbiome‐based classification of CVD and non‐CVD. We analyzed 16S rRNA sequencing data of stool samples collected from 305 CVD males, 213 non‐CVD males, 169 CVD females and 259 non‐CVD females through the American Gut Project. We identified 62 differential bacterial taxa with a score of linear discriminant analysis effect size (LDA) more than 2.0 between the female CVD and non‐CVD groups (Figure 1A), whereas 33 differential bacterial features (LDA > 2.0) between the male CVD and non‐CVD groups (Figure 1B). Genera Bacteroides , Subdoligranulum and Citrobacter were found to be more abundant in female CVD patients, whereas Pseudomonas , Akkermansia , and Clostridium were more abundant in male CVD patients. Interestingly, Clostridium, which was previously reported to be associated with heart failure and cardiomyopathy, was the only bacterial taxa identified to be enriched in both male and female CVD groups, indicating clear sex differences in gut microbiome dysbiosis between individuals with or without CVD. As our previous work demonstrates the promising application of gut microbiome‐based machine learning for the detection of CVD, the current study further reveals the importance of segregating sex as a discriminative feature for improving microbiome‐based diagnostics of CVD.